Monte Carlo simulation as a service in the Cloud. (2015)

• Record Type: Journal Article
• Authors: Chang, Victor; Walters, Robert John; Wills, Gary
• Is Part Of: International journal of business process integration and management. Volume 7:Number 3(2015)
• Page Start: 262
• Page End: 271
• Publication Date: 2015
• Subjects: Monte Carlo methods -- MCM -- Monte Carlo simulation as a service -- MCSaaS -- least squares methods -- LSMs -- Gaussian copula -- cloud services -- cloud computing; Business -- Computer networks -- Periodicals; Industrial management -- Periodicals; 658.054605
• Languages: English
• ISSNs: 1741-8763

Abstract

We propose a Monte Carlo simulation as a service (MCSaaS) which takes the benefits from two sides: the accuracy and reliability of typical Monte Carlo simulations and the fast performance of offering services in the Cloud. In the use of MCSaaS, we propose to remove outliers to enhance the improvement in accuracy. We propose three hypotheses and describe our rationale, architecture and steps involved for validation. We set up three major experiments. We confirm that firstly, MCSaaS with outlier removal reduces percentage of errors to 0.1%. Secondly, MCSaaS with outlier removal is expected to have slower performance than the one without removal but is kept within one second difference. Thirdly, MCSaaS in the Cloud has a significant performance improvement over a popular model on desktop. We demonstrate our approach can meet the demands for accuracy and performance.